apis/examples_matlab_control/transport4_8m_source.html

function transport4(varargin)


    % check workspace info from arguments

    if nargin > 0

        wsInfo = gams.control.WorkspaceInfo();

        wsInfo.systemDirectory = varargin{1};

        ws = gams.control.Workspace(wsInfo);

    else

        ws = gams.control.Workspace();

    end


    model = {

    'Sets                                                                       '

    '      i   canning plants                                                   '

    '      j   markets                                                          '

    '                                                                           '

    ' Parameters                                                                '

    '      a(i)   capacity of plant i in cases                                  '

    '      b(j)   demand at market j in cases                                   '

    '      d(i,j) distance in thousands of miles                                '

    ' Scalar f  freight in dollars per case per thousand miles;                 '

    '                                                                           '

    '$if not set gdxincname $abort ''no include file name for data file provided'''

    '$gdxin %gdxincname%                                                        '

    '$load i j a b d f                                                          '

    '$gdxin                                                                     '

    '                                                                           '

    ' Parameter c(i,j)  transport cost in thousands of dollars per case ;       '

    '                                                                           '

    '            c(i,j) = f * d(i,j) / 1000 ;                                   '

    '                                                                           '

    ' Variables                                                                 '

    '       x(i,j)  shipment quantities in cases                                '

    '       z       total transportation costs in thousands of dollars ;        '

    '                                                                           '

    ' Positive Variable x ;                                                     '

    '                                                                           '

    ' Equations                                                                 '

    '                                                                           '

    '      cost        define objective function                                '

    '      supply(i)   observe supply limit at plant i                          '

    '      demand(j)   satisfy demand at market j ;                             '

    '                                                                           '

    '  cost ..        z  =e=  sum((i,j), c(i,j)*x(i,j)) ;                       '

    '                                                                           '

    '  supply(i) ..   sum(j, x(i,j))  =l=  a(i) ;                               '

    '                                                                           '

    '  demand(j) ..   sum(i, x(i,j))  =g=  b(j) ;                               '

    '                                                                           '

    ' Model transport /all/ ;                                                   '

    '                                                                           '

    ' Solve transport using lp minimizing z ;                                   '

    '                                                                           '

    ' Display x.l, x.m ;                                                        '};

    model = sprintf('%s\n', model{:});


    % prepare input data

    plants = {'Seattle', 'San-Diego'};

    markets = {'New-York', 'Chicago', 'Topeka'};

    capacity = containers.Map();

    capacity('Seattle') = 350;

    capacity('San-Diego') = 600;

    demand = containers.Map();

    demand('New-York') = 325;

    demand('Chicago') = 300;

    demand('Topeka') = 275;

    distance = containers.Map();

    distance('Seattle.New-York') = 2.5;

    distance('Seattle.Chicago') = 1.7;

    distance('Seattle.Topeka') = 1.8;

    distance('San-Diego.New-York') = 2.5;

    distance('San-Diego.Chicago') = 1.8;

    distance('San-Diego.Topeka') = 1.4;


    % add a database and add input data into the database

    db = ws.addDatabase();


    i = db.addSet('i', 1, 'canning plants');

    for p = plants

        i.addRecord(p{1});

    end


    j = db.addSet('j', 1, 'markets');

    for m = markets

        j.addRecord(m{1});

    end


    a = db.addParameter('a', 'capacity of plant i in cases', i);

    for p = plants

        rec = a.addRecord(p{1});

        rec.value = capacity(p{1});

    end


    b = db.addParameter('b', 'demand at market j in cases', j);

    for m = markets

        rec = b.addRecord(m{1});

        rec.value = demand(m{1});

    end


    d = db.addParameter('d', 'distance in thousands of miles', i, j);

    for p = plants

        for m = markets

            rec = d.addRecord(p{1}, m{1});

            rec.value = distance([p{1}, '.', m{1}]);

        end

    end


    f = db.addParameter('f', 'freight in dollars per case per thousand miles');

    rec = f.addRecord();

    rec.value = 90;


    % create and run a job from the model and read gdx include file from the database

    t4 = ws.addJobFromString(model);

    opt = ws.addOptions();

    opt.defines('gdxincname', db.name);

    t4.run(opt, db);


    % retrieve Variable 'x' from Job's output databases

    fprintf('\nRan with Default:\n');

    for x = t4.outDB.getVariable('x').records

        fprintf('x(%s,%s): level=%g marginal=%g\n', x{1}.keys{:}, x{1}.level, x{1}.marginal);

    end


    % clear database

    t4.outDB.dispose();


    % set option of all model types for xpress and run the job again

    opt.setAllModelTypes('xpress');

    t4.run(opt, db);


    % retrieve Variable 'x' from Job's output databases

    fprintf('\nRan with XPRESS:\n');

    for x = t4.outDB.getVariable('x').records

        fprintf('x(%s,%s): level=%g marginal=%g\n', x{1}.keys{:}, x{1}.level, x{1}.marginal);

    end


    % clear option and database

    opt.dispose();

    db.dispose();

    t4.outDB.dispose();


    % remove working directory

    rmdir(ws.workingDirectory, 's');


end